Guides articles

How to use kubectl run

Use kubectl run to create quick pods for testing images, commands, ports, and dry-run manifests in a Kubernetes cluster.

How to use the Kubernetes control plane

Understand the Kubernetes control plane, its core components, and the operational practices that keep scheduling and reconciliation healthy.

StatefulSet vs. Deployment: differences and use cases

Compare Kubernetes StatefulSets and Deployments, including identity, storage, scaling, rollout behavior, and common use cases.

Kubernetes deployments: a complete guide

Learn how Kubernetes Deployments manage pods and ReplicaSets, support rollout strategies, and keep applications available.

Kubernetes architecture for ML workloads

A practical overview of Kubernetes architecture and how its control plane, worker nodes, services, and storage affect ML workloads.

Container orchestration: benefits and tutorial

Container orchestration automates scheduling, scaling, networking, and recovery for containerized applications running across clusters.

Kubernetes Workloads Basics

Kubernetes fundamental notions and basics of workloads for data-scientists and machine learning engineers.

Train and deploy machine learning applications to Kubernetes using Streamlit and Polyaxon

A step-by-step guide to train, analyze, and deploy a containerized Streamlit machine learning application on Kubernetes using Polyaxon.

Troubleshooting Kubernetes for data-scientists

Troubleshooting machine learning (ML) and deep learning(DL) workload on Kubernetes for data-scientists and machine learning engineers.

Common Git commands for data-scientists

Common Git commands for data-scientists and machine learning engineers

Common Docker terms for data-scientists

Common Docker terms for data-scientists and machine learning engineers

Machine learning workload on Kubernetes

Scheduling and orchestrating machine learning (ML) and deep learning(DL) workload workload on Kubernetes.

Common Git terms for data-scientists

Common Git terms for data-scientists and machine learning engineers

Docker for data-scientists

Basic Docker concepts for data-scientists and machine learning engineers

Kubernetes for data-scientists

Basic concepts of Kubernetes for data-scientists and machine learning engineers to manage machine learning (ML) and deep learning(DL) workload and applications.

Git for data-scientists

Basic Git concepts for data-scientists and machine learning engineers

Install Polyaxon on MicroK8s

This is a guide to assist you through the process of setting up a Polyaxon deployment using MicroK8s.

Install Polyaxon using kubeadm on Kubernetes

This is a guide to assist you through the process of setting up a Polyaxon deployment using kubeadm and Kubernetes.

Install Polyaxon on Minikube

This is a guide to assist you through the process of setting up a Polyaxon deployment using Minikube.

Autoscaling of preemptible GPU resources

Discussion about how to use a pool of preemptible GPUs that are automatically used whenever experiments or a hyperparameter search is created in Polyaxon.